1. Clearing the Path for Data Discovery and Re-Use Thomson Reuters Panel Discussion: Libraries Taking a Leading Role in Data Curation and Preservation Elizabeth Moss ICPSR eammoss@umich.edu ALA Annual Conference June 24, 2012

2. Overview 1.About ICPSR and the data we archive 2.Data discovery with the Bibliography of Data-related Literature 3.Aiding the cultural shift to reliable data citing practice

3. What is ICPSR? 50 Years of Data Management One of the world’s oldest and largest social science data archives, est. 1962 Data distributed on punch cards, then reel- to-reel tape, now: –Data available on demand, online –Over 8,000 studies with over 65,000 data sets Membership organization started among 21 universities, now: –Over 700 members world-wide –Federal funding of public collections

6. Data Sharing Increases Research Productivity... The majority of social science data are not archived publicly Younger researchers are more protective of their research than established ones When data are archived (formally), 2-3 times more publications are created -- Pienta, Amy M.; Alter, George C.; Lyle, Jared A. (2010) The enduring value of social science research: The use and reuse of primary research data. http://hdl.handle.net/2027.42/78307http://hdl.handle.net/2027.42/78307

7. Top 10 Downloads This Year 1.National Survey on Drug Use and Health, 2010 2.National Longitudinal Study of Adolescent Health (Add Health), 1994-2008 3.General Social Survey (1972-2010) 4.Chinese Household Income Survey, 2002 5.India Human Development Survey (IHDS), 2005 6.Collaborative Psychiatric Epidemiology Surveys (CPES), 2001-2003 7.National Crime Victimization Survey, 2010 8.Children of Immigrants Longitudinal Study (CILS), 1991- 2006 9.National Survey on Drug Use and Health, 2009 10.The 500 Family Study, 1998-2000

10. In References, with DOI doi:10.3886/ICPSR21240

12. Finding Cited Data in the Social Science Research Literature

13. Abstract? Acknowledgements? Charts and Tables? Appendices ? References! Discussion? Footnotes? Sample? Methods? Data “Sighting” (implicit) vs. Data Citing (explicit)

14. Issues with Attribution and Access Sample described, not named, no author information, no access information, only a publication cited Data named in text, with some attribution, but no access information Cited in reference section, but with no permanent, unique identifier

22. Other efforts to

24. IASSIST Special Interest Group on Data Citation

26. Contact Information Jared Lyle: lyle@umich.edu Data Management Planning Amy Pienta: apienta@umich.edu Depositing Data at ICPSR Mary Vardigan: vardigan@umich.edu DDI and Metadata Elizabeth Moss: eammoss@umich.edu ICPSR Bibliography of Data-related Literature

27. Thank you!